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arXiv · 2202.00048

Single Time-scale Actor-critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees

Mo Zhou·Jianfeng Lu
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Abstract

We propose a single time-scale actor-critic algorithm to solve the linear quadratic regulator (LQR) problem. A least squares temporal difference (LSTD) method is applied to the critic and a natural policy gradient method is used for the actor. We give a proof of convergence with sample complexity $\mathcal{O}(\varepsilon^{-1} \log(\varepsilon^{-1})^2)$. The method in the proof is applicable to general single time-scale bilevel optimization problem. We also numerically validate our theoretical results on the convergence.

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Mo Zhou, Jianfeng Lu. 2022-01-31. Single Time-scale Actor-critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees. https://arxiv.org/abs/2202.00048

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